Autonomous agents, such as robots, robotic vehicles, or software agents, may coordinate the performance of shared or interdependent tasks through a central node. The central node communicates with each of the autonomous agents to determine the status of each of the autonomous agents to determine when the autonomous agents are prepared to perform a task and then communicates with each of the autonomous agents to initiate a next action. The central node acts as a central “blackboard” where each of the autonomous agents can post its status and review the status of the other autonomous agents.
Reliance on a central node presents certain disadvantages. For example, because each of the autonomous agents is dependent upon the central node for communication, if the central node fails, the autonomous agents may not be able to perform tasks. As another example, reliance on a central node may limit scalability of a system because a central node may only be able to reasonably maintain communication with a limited number of autonomous agents before communications interference or contention results in inefficient operations. Similarly, if each of the autonomous agents must maintain communications with the central node, the transmissions range of the central node may limit the size of the area in which the autonomous agents can perform shared or interdependent tasks.
Distributed systems in which autonomous agents may act independently of a central node resolve some of these concerns. However, even if the autonomous agents may act without reliance on a central node, if each of the autonomous agents must confer with every other autonomous agents to determine the status of the other autonomous agents these restrictions may limit system scalability and area coverage.